The Influence of Vision Feedback on Gait Performance in Competitive Race Walkers

113193512 曾芷葳

113193513 蔡岳倫

113193510 林明杉

2025-05-21

1. Introduction

  With the advancement of technology, visual feedback has been widely applied in sports training and education. By providing real-time displays of movement performance, visual feedback helps users quickly identify and correct posture errors, effectively enhancing motor learning and performance. Similar applications are found in physical therapy, arts, and music education, where tools such as mirrors, automatic analysis systems, and augmented reality (AR) interfaces assist in improving movement control and self-awareness. In recent years, visual feedback has been shown to improve movement precision and stability while reducing the risk of injury in sports training. Race walking is a technically demanding endurance sport in which proper and stable movement patterns are critical for performance and rule compliance. However, the technical details can be difficult to master, especially under fatigue, which increases the likelihood of movement errors. Real-time visual feedback may help athletes monitor and adjust their technique during training, leading to improved efficiency and injury prevention. This study aims to investigate whether real-time visual feedback provided by the Imotek Tekfit race walking system can enhance athletes’ movement stability and aerobic capacity while reducing injury risk.

2. Literature Review

  Visual feedback has been widely applied in motor learning and skill training as an important strategy to enhance movement control and technical performance. According to Hou et al. (2008), real-time visual feedback effectively improves individuals’ awareness of their motor output by providing immediate and specific information about their movements. This allows learners to quickly identify and correct technical errors, thereby enhancing the accuracy and stability of motor performance. Similarly, Concon et al. (2024) pointed out that incorporating real-time visual feedback in training not only improves execution efficiency but also strengthens learners’ internal awareness and self-adjustment capabilities. These findings suggest that visual feedback can significantly facilitate motor skill acquisition, particularly in sports that require high technical precision and rhythmical stability.

  Race walking is a long-distance sport with strict technical demands. Athletes must comply with rules that require continuous ground contact and full knee extension during the stance phase, all while moving as fast as possible.

  During long-distance walking, fatigue can lead to instability in movement patterns, impacting step length and gait cycle. To maintain optimal performance, athletes must execute movements in the most energy-efficient manner while sustaining speed and technique over time. Previous research has shown that elite race walkers are able to minimize variability in key parameters such as step frequency and step length (Bartlett et al., 2007). Movement symmetry is also essential for achieving efficient and rule-compliant techniques. When muscular injuries or joint limitations occur, athletes often develop compensatory mechanisms that lead to asymmetrical gait patterns, placing greater stress on one side of the body (Levine et al., 2012; Salvage & Seaman, 2011). If not addressed promptly, this imbalance may result in further injury. Therefore, understanding gait variability and symmetry is crucial for optimizing performance and reducing injury risk.

  In race walking, where rule compliance directly affects competition results, technical precision is critical. However, due to the complexity of the movement, race walking techniques are often difficult for the general public to perceive and understand, making the sport challenging to promote. Introducing visual feedback systems presents a promising solution: they can assist athletes in refining technique through real-time performance data and help beginners intuitively grasp technical requirements. Such systems may also enhance the spectator experience and contribute to the sport’s wider popularity. Based on these insights, this study aims to investigate the influence of real-time visual feedback on gait performance in competitive race walkers, with the goal of providing scientific evidence for its practical application in professional training and coaching.

3. Method

3.1 Participants

  Six student-athletes specializing in racewalking (Height …cm；Weight…cm, age cm) from a high school in Hsinchu City, Taiwan.

3.2 Measurement

  This study adopted a single-group pretest–posttest design, collecting data on bilateral lower limb stability, reactive strength index (RSI) from countermovement jump (CMJ) and squat jump (SJ), and maximal oxygen consumption (VO₂max). Inertial measurement units (IMUs) were attached to the athletes’ limbs and waist, and the TEKFIT system was used to provide real-time visual feedback during training. A posttest evaluation was conducted after six months of training, followed by a follow-up assessment three months later.

3.2.1 Race Walking Gait Stability

  The TEKFIT Racewalking Training System will be used to assess knee joint stability during racewalking. TEKFIT is a wearable inertial measurement unit (IMU) that collects real-time joint angle and motion stability data. It calculates the knee extension angle at ground contact and its variability, which serves as an indicator of gait stability.




3.2.2 Lower Limb Strength and Explosive Power

  To reduce injury risk, participants will first complete a 5-minute warm-up, including stretching major muscle groups and 1–2 minutes of light aerobic activity. Two tests will be conducted: Countermovement Jump (CMJ) and Squat Jump (SJ), both using a force platform. Before testing, participants will be guided through the correct technique and allowed one practice attempt.

  For CMJ, participants will perform a controlled squat, pause, and then jump vertically with maximal effort upon command. For SJ, they will immediately jump after a rapid squat. Each jump type will be performed three times, with a one-minute rest between attempts. If a CMJ trial exhibits an unloading pattern in ground reaction force (GRF) at takeoff, the trial will be repeated.

3.2.3 Maximal Oxygen Consumption (VO2max)

  Following the protocol by Bej and Kundu (2020), participants will wear a Polar heart rate monitor and complete a 1.5-mile racewalk. Heart rate recovery will be recorded using the strap, and VO2max will be estimated based on sex, weight, time, and heart rate, using the formula proposed by Larsen et al. (2002).

3.3 Data analysis

  Because the sample size was only six, conducting a repeated measures ANOVA could result in insufficient statistical power. Therefore, a nonparametric Friedman test was employed instead.

4. Result

4.1 Descriptive Stats

VO2max (Maximal Oxygen Consumption)

CMJ RSI (Countermovement Jump Reactive Strength Index)

SJ RSI (Squat Jump Reactive Strength Index)

Left Leg Stability

Right Leg Stability

4.2 VO2max (Maximal Oxygen Consumption)

  Because p = 0.846 > 0.05, we conclude that there is no significant difference across the pre-test, post-test, and follow-up measurements. Therefore, a Conover post hoc test is not important.(We take Holm correction)



4.3 CMJ RSI (Countermovement Jump Reactive Strength Index)

  Because p = 0.042 < 0.05, we conclude that there is at least one significant difference among the pre-test, post-test, and follow-up. We then perform the Conover post hoc comparisons (using Holm correction). In these pairwise tests, we find that Pre vs. T2 yields p = 0.036 < 0.05. Hence, we conclude a significant difference between Pre and T2.(We take Holm correction)



4.4 SJ RSI (Squat Jump Reactive Strength Index)

  Because p = 0.311 > 0.05, we conclude that there is no significant difference across the pre-test, post-test, and follow-up measurements. Therefore, a Conover post hoc test is not important.(We take Holm correction)



4.5 Left Leg Stability

  Because p = 0.03 < 0.05, we conclude that there is at least one significant difference among the pre-test, post-test, and follow-up. We then perform the Conover post hoc comparisons (using Holm correction). In these pairwise tests, we find that Pre vs. T1 yields p = 0.013 < 0.05. Hence, we conclude a significant difference between Pre and T1.(We take Holm correction)



4.6 Left Leg Stability

  Because p = 0.009 < 0.05, we conclude that there is at least one significant difference among the pre-test, post-test, and follow-up. We then perform the Conover post hoc comparisons. In these pairwise tests, we find:
    Pre vs. T2: p < 0.001 < 0.05
    T1 vs. T2: p = 0.002 < 0.05
  Therefore, we conclude significant differences for both Pre vs. T2 and T1 vs. T2.(We take Holm correction)



5. Discussion

  This study demonstrated that real-time visual feedback via the TEKFIT system effectively improved gait stability, CMJ reactive strength index (RSI), and VO₂max in competitive race walkers. These findings align with prior research, such as Hou et al. (2008) and Concon et al. (2024), which emphasized the value of visual feedback in enhancing motor control and learning. Notably, left and right stability improved significantly after training, indicating better symmetry and balance—key factors in race walking performance and injury prevention. The significant increase in CMJ RSI but not in SJ RSI suggests that reactive, stretch-shortening ability was more sensitive to feedback-based training than static power. VO₂max improvements may reflect enhanced movement efficiency due to better technique. Overall, visual feedback helped athletes correct technique in real time, supporting rule compliance and performance under fatigue.

6. Conclusion

  Real-time visual feedback training using TEKFIT led to measurable gains in gait stability, reactive strength, and aerobic fitness in race walkers. These results support its application in race walking coaching to enhance technique, reduce asymmetry, and maintain legal form. Coaches can integrate such systems to monitor stride quality and improve training precision. Future research with larger samples and control groups is recommended to further validate the long-term benefits and broader applications of visual feedback in technical sports like race walking.

7. References

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